a. Field of the Invention
This invention relates to the field of multiprocessing systems and error recovery in multiprocessing systems.
b. Related Art
A multiprocessing system (MPS) is a computing system employing two or more connected processing units to execute programs simultaneously. Conventionally, multiprocessing systems have been classified into a number of types based on the interconnection between the processors.
A first type of conventional multiprocessing system is the "multiprocessor" or "shared memory" system (FIG. 1). In a shared memory system, number of central processing units 102-106 are interconnected by the fact that they share a common global memory 108. Although each central processing unit may have a local cache memory, cross cache validation makes the caches transparent to the user and the system appears as if it only has a single global memory.
Shared memory systems also take the form of multiple central processing units sharing multiple global memories through a connection network. An example of such a system is an Omega network (FIG. 2). In an Omega network a plurality of switches S01-S24 organized into stages route data between a plurality of processors P0-P7 and a plurality of global memories M0-M7 by using a binary destination tag generated by a requesting processor. Each stage of switches in the network decodes a respective bit of the tag to make the network self-routing. The Omega network thereby avoids the need for a central controller.
A common characteristic of shared memory systems is that access time to a piece of data in the memory is independent of the processor making the request. A significant limitation of shared memory systems is that the aggregate bandwidth of the global memory limits the number of processors that can be effectively accommodated on the system.
A second type of commonly known multiprocessing system is the multicomputer message passing network (FIG. 3). Message passing networks are configured by interconnecting a number of processing nodes. Each node 302-308 includes a central processing unit and a local memory that is not globally accessible. In order for an application to share data among processors the programmer must explicitly code commands to move data from one node to another. In contrast to shared memory systems, the time that it takes for a processor to access data depends on its distance (in nodes) from the processor that currently has the data in its local memory.
In the message passing network configuration of FIG. 3, each node has a direct connection to every other node. Such configurations are, however, impractical for large number of processors. Solutions such as hypercube configurations have been conventionally used to limit the largest distance between processors. In any event, as the number of processors in the network increases the number of indirect connections and resulting memory access times will also tend to increase.
A third type of multiprocessing system is the hybrid machine (FIG. 4). Hybrid machines have some of the properties of shared memory systems and some of the properties of message passing networks. In the hybrid machine, a number of processors 402-406, each having a local memory, are connected by way of a connection network 408. Even though all memories are local, the operating system makes the machine look like at has a single global memory. An example of a Hybrid machine is the IBM RP3. Hybrid machines can typically provide access to remote data significantly faster than message passing networks. Even so, data layout can be critical to algorithm performance and the aggregate communications speed of the connection network is a limit to the number of processors that can be effectively accommodated.
A variant on multiprocessing system connection networks is the cluster-connected network (FIG. 5). In a cluster-connected networks, a number of clusters 502-508, each including a group of processors 510-516 and a multiplexer/controller 518, are connected through switch network 520. The cluster network has advantages over the topology of FIG. 4 in that a larger number of processors can be effectively connected to the switch network through a given number of ports. One constraint of cluster connected networks is that the bandwidths of both the cluster controller and the switch are critical to system performance. For this reason, the design of the switch and cluster controller are important factors in determining maximum system size and performance.